Overview

Dataset statistics

Number of variables30
Number of observations1563215
Missing cells1827272
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory357.8 MiB
Average record size in memory240.0 B

Variable types

Numeric11
Categorical18
Boolean1

Alerts

WORK GROUP has a high cardinality: 146 distinct valuesHigh cardinality
REQUEST TYPE has a high cardinality: 1236 distinct valuesHigh cardinality
CATEGORY has a high cardinality: 84 distinct valuesHigh cardinality
TYPE has a high cardinality: 295 distinct valuesHigh cardinality
DETAIL has a high cardinality: 574 distinct valuesHigh cardinality
CREATION DATE has a high cardinality: 5229 distinct valuesHigh cardinality
CREATION TIME has a high cardinality: 1440 distinct valuesHigh cardinality
CLOSED DATE has a high cardinality: 4995 distinct valuesHigh cardinality
STREET ADDRESS has a high cardinality: 277728 distinct valuesHigh cardinality
ADDRESS WITH GEOCODE has a high cardinality: 307249 distinct valuesHigh cardinality
NEIGHBORHOOD has a high cardinality: 250 distinct valuesHigh cardinality
CASE URL has a high cardinality: 1563215 distinct valuesHigh cardinality
SOURCE is highly imbalanced (72.5%)Imbalance
DEPARTMENT is highly imbalanced (55.9%)Imbalance
STATUS is highly imbalanced (94.2%)Imbalance
COUNTY is highly imbalanced (74.4%)Imbalance
CLOSED MONTH has 26515 (1.7%) missing valuesMissing
CLOSED YEAR has 26515 (1.7%) missing valuesMissing
DAYS TO CLOSE has 26515 (1.7%) missing valuesMissing
NEIGHBORHOOD has 46106 (2.9%) missing valuesMissing
COUNTY has 66959 (4.3%) missing valuesMissing
COUNCIL DISTRICT has 35242 (2.3%) missing valuesMissing
POLICE DISTRICT has 35265 (2.3%) missing valuesMissing
30-60-90 Days Open Window has 1550513 (99.2%) missing valuesMissing
ZIP CODE is highly skewed (γ1 = -832.06849)Skewed
PARCEL ID NO is highly skewed (γ1 = 250.9088658)Skewed
CASE URL is uniformly distributedUniform
CASE ID has unique valuesUnique
CASE URL has unique valuesUnique
DAYS TO CLOSE has 150614 (9.6%) zerosZeros
PARCEL ID NO has 35266 (2.3%) zerosZeros

Reproduction

Analysis started2023-02-25 15:09:55.053730
Analysis finished2023-02-25 15:12:13.662627
Duration2 minutes and 18.61 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

CASE ID
Real number (ℝ)

Distinct1563215
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0140133 × 109
Minimum2.006 × 109
Maximum2.0210337 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:13.728845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.006 × 109
5-th percentile2.0071832 × 109
Q12.0101856 × 109
median2.0140975 × 109
Q32.0180632 × 109
95-th percentile2.0200896 × 109
Maximum2.0210337 × 109
Range15033684
Interquartile range (IQR)7877594

Descriptive statistics

Standard deviation4222588.7
Coefficient of variation (CV)0.0020966042
Kurtosis-1.3391166
Mean2.0140133 × 109
Median Absolute Deviation (MAD)3950638
Skewness-0.072037995
Sum3.1483358 × 1015
Variance1.7830256 × 1013
MonotonicityNot monotonic
2023-02-25T10:12:13.804384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019119972 1
 
< 0.1%
2015045877 1
 
< 0.1%
2015040302 1
 
< 0.1%
2015041682 1
 
< 0.1%
2015049038 1
 
< 0.1%
2015034811 1
 
< 0.1%
2015041579 1
 
< 0.1%
2015042453 1
 
< 0.1%
2015052481 1
 
< 0.1%
2015043953 1
 
< 0.1%
Other values (1563205) 1563205
> 99.9%
ValueCountFrequency (%)
2006000002 1
< 0.1%
2006000004 1
< 0.1%
2007000001 1
< 0.1%
2007000005 1
< 0.1%
2007000009 1
< 0.1%
2007000010 1
< 0.1%
2007000012 1
< 0.1%
2007000013 1
< 0.1%
2007000014 1
< 0.1%
2007000015 1
< 0.1%
ValueCountFrequency (%)
2021033686 1
< 0.1%
2021033407 1
< 0.1%
2021033233 1
< 0.1%
2021033140 1
< 0.1%
2021032869 1
< 0.1%
2021032828 1
< 0.1%
2021032612 1
< 0.1%
2021032575 1
< 0.1%
2021032525 1
< 0.1%
2021032480 1
< 0.1%

SOURCE
Categorical

Distinct21
Distinct (%)< 0.1%
Missing67
Missing (%)< 0.1%
Memory size11.9 MiB
PHONE
1204236 
WEB
211721 
EMAIL
 
80585
SYS
 
19226
INSPE
 
14690
Other values (16)
 
32690

Length

Max length5
Median length5
Mean length4.677877
Min length3

Characters and Unicode

Total characters7312214
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPHONE
2nd rowWEB
3rd rowPHONE
4th rowPHONE
5th rowWEB

Common Values

ValueCountFrequency (%)
PHONE 1204236
77.0%
WEB 211721
 
13.5%
EMAIL 80585
 
5.2%
SYS 19226
 
1.2%
INSPE 14690
 
0.9%
BOT 13396
 
0.9%
TWIR 8311
 
0.5%
VOICE 6021
 
0.4%
WALK 1792
 
0.1%
FAX 1538
 
0.1%
Other values (11) 1632
 
0.1%

Length

2023-02-25T10:12:13.880472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
phone 1204236
77.0%
web 211721
 
13.5%
email 80585
 
5.2%
sys 19226
 
1.2%
inspe 14690
 
0.9%
bot 13396
 
0.9%
twir 8311
 
0.5%
voice 6021
 
0.4%
walk 1792
 
0.1%
fax 1538
 
0.1%
Other values (11) 1632
 
0.1%

Most occurring characters

ValueCountFrequency (%)
E 1518427
20.8%
O 1223712
16.7%
P 1219913
16.7%
N 1218950
16.7%
H 1204260
16.5%
B 225129
 
3.1%
W 221824
 
3.0%
I 110312
 
1.5%
A 84238
 
1.2%
L 82700
 
1.1%
Other values (12) 202749
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7312214
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1518427
20.8%
O 1223712
16.7%
P 1219913
16.7%
N 1218950
16.7%
H 1204260
16.5%
B 225129
 
3.1%
W 221824
 
3.0%
I 110312
 
1.5%
A 84238
 
1.2%
L 82700
 
1.1%
Other values (12) 202749
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 7312214
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1518427
20.8%
O 1223712
16.7%
P 1219913
16.7%
N 1218950
16.7%
H 1204260
16.5%
B 225129
 
3.1%
W 221824
 
3.0%
I 110312
 
1.5%
A 84238
 
1.2%
L 82700
 
1.1%
Other values (12) 202749
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7312214
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 1518427
20.8%
O 1223712
16.7%
P 1219913
16.7%
N 1218950
16.7%
H 1204260
16.5%
B 225129
 
3.1%
W 221824
 
3.0%
I 110312
 
1.5%
A 84238
 
1.2%
L 82700
 
1.1%
Other values (12) 202749
 
2.8%

DEPARTMENT
Categorical

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
NHS
783094 
Public Works
353787 
Water Services
216852 
Parks and Rec
87954 
Health
 
39543
Other values (22)
81985 

Length

Max length35
Median length3
Mean length7.6318446
Min length2

Characters and Unicode

Total characters11930214
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowNHS
2nd rowPublic Works
3rd rowNHS
4th rowNHS
5th rowParks and Rec

Common Values

ValueCountFrequency (%)
NHS 783094
50.1%
Public Works 353787
22.6%
Water Services 216852
 
13.9%
Parks and Rec 87954
 
5.6%
Health 39543
 
2.5%
KCPD 36369
 
2.3%
City Managers Office 13098
 
0.8%
City Planning and Development 12575
 
0.8%
Northland 8591
 
0.5%
NCS 6391
 
0.4%
Other values (17) 4961
 
0.3%

Length

2023-02-25T10:12:13.947657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nhs 783094
32.9%
public 353787
14.9%
works 353787
14.9%
water 216852
 
9.1%
services 216852
 
9.1%
and 100588
 
4.2%
parks 88826
 
3.7%
rec 88815
 
3.7%
health 39543
 
1.7%
kcpd 36369
 
1.5%
Other values (32) 98741
 
4.2%

Most occurring characters

ValueCountFrequency (%)
S 1007164
 
8.4%
r 900261
 
7.5%
e 847896
 
7.1%
H 822980
 
6.9%
814039
 
6.8%
N 798111
 
6.7%
c 675143
 
5.7%
s 672981
 
5.6%
i 626675
 
5.3%
W 570639
 
4.8%
Other values (30) 4194325
35.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7151431
59.9%
Uppercase Letter 3963872
33.2%
Space Separator 814039
 
6.8%
Other Punctuation 872
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 900261
12.6%
e 847896
11.9%
c 675143
9.4%
s 672981
9.4%
i 626675
8.8%
a 496002
 
6.9%
k 442615
 
6.2%
l 427997
 
6.0%
o 376777
 
5.3%
u 355543
 
5.0%
Other values (11) 1329541
18.6%
Uppercase Letter
ValueCountFrequency (%)
S 1007164
25.4%
H 822980
20.8%
N 798111
20.1%
W 570639
14.4%
P 491557
12.4%
R 88827
 
2.2%
C 69282
 
1.7%
D 49286
 
1.2%
K 36369
 
0.9%
M 13514
 
0.3%
Other values (7) 16143
 
0.4%
Space Separator
ValueCountFrequency (%)
814039
100.0%
Other Punctuation
ValueCountFrequency (%)
& 872
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11115303
93.2%
Common 814911
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 1007164
 
9.1%
r 900261
 
8.1%
e 847896
 
7.6%
H 822980
 
7.4%
N 798111
 
7.2%
c 675143
 
6.1%
s 672981
 
6.1%
i 626675
 
5.6%
W 570639
 
5.1%
a 496002
 
4.5%
Other values (28) 3697451
33.3%
Common
ValueCountFrequency (%)
814039
99.9%
& 872
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11930214
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 1007164
 
8.4%
r 900261
 
7.5%
e 847896
 
7.1%
H 822980
 
6.9%
814039
 
6.8%
N 798111
 
6.7%
c 675143
 
5.7%
s 672981
 
5.6%
i 626675
 
5.3%
W 570639
 
4.8%
Other values (30) 4194325
35.2%

WORK GROUP
Categorical

Distinct146
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
NHS-Neighborhood Preservation-
286049 
NHS-Solid Waste-
238286 
NHS-Animal Health and Safety-
136453 
Public Works-Solid Waste-
99384 
Water Services-Meter and Field Services-
88432 
Other values (141)
714611 

Length

Max length50
Median length47
Mean length31.048004
Min length6

Characters and Unicode

Total characters48534706
Distinct characters53
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowNHS-Dangerous Buildings-
2nd rowPublic Works-Street and Traffic-District 1
3rd rowNHS-Dangerous Buildings-
4th rowNHS-Neighborhood Preservation-
5th rowParks and Rec-Central Region-

Common Values

ValueCountFrequency (%)
NHS-Neighborhood Preservation- 286049
18.3%
NHS-Solid Waste- 238286
15.2%
NHS-Animal Health and Safety- 136453
 
8.7%
Public Works-Solid Waste- 99384
 
6.4%
Water Services-Meter and Field Services- 88432
 
5.7%
Parks and Rec-Landscape Services-Forestry 65660
 
4.2%
NHS-Solid Waste-Administration 44450
 
2.8%
Public Works-Street and Traffic-District 3 40955
 
2.6%
Water Services-Line Maintenance-Wastewater 39641
 
2.5%
Public Works-Street and Traffic-Streetlights 38108
 
2.4%
Other values (136) 485797
31.1%

Length

2023-02-25T10:12:14.021815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
and 497876
 
10.5%
public 353787
 
7.5%
waste 337776
 
7.2%
nhs-neighborhood 317500
 
6.7%
nhs-solid 299322
 
6.3%
preservation 286854
 
6.1%
water 216852
 
4.6%
works-street 159398
 
3.4%
health 143813
 
3.0%
nhs-animal 139749
 
3.0%
Other values (206) 1968123
41.7%

Most occurring characters

ValueCountFrequency (%)
e 4530059
 
9.3%
i 3300515
 
6.8%
r 3283333
 
6.8%
a 3180184
 
6.6%
3157835
 
6.5%
- 3121076
 
6.4%
t 2853937
 
5.9%
o 2635467
 
5.4%
s 2190723
 
4.5%
n 2099413
 
4.3%
Other values (43) 18182164
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34166821
70.4%
Uppercase Letter 7973083
 
16.4%
Space Separator 3157835
 
6.5%
Dash Punctuation 3121076
 
6.4%
Decimal Number 114274
 
0.2%
Other Punctuation 1617
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4530059
13.3%
i 3300515
9.7%
r 3283333
9.6%
a 3180184
9.3%
t 2853937
8.4%
o 2635467
 
7.7%
s 2190723
 
6.4%
n 2099413
 
6.1%
l 1550002
 
4.5%
d 1511973
 
4.4%
Other values (14) 7031215
20.6%
Uppercase Letter
ValueCountFrequency (%)
S 2058471
25.8%
N 1136393
14.3%
W 1020241
12.8%
P 1005647
12.6%
H 976676
12.2%
C 262046
 
3.3%
A 220751
 
2.8%
M 215408
 
2.7%
T 213447
 
2.7%
L 202835
 
2.5%
Other values (13) 661168
 
8.3%
Decimal Number
ValueCountFrequency (%)
3 50862
44.5%
1 39053
34.2%
2 24359
21.3%
Space Separator
ValueCountFrequency (%)
3157835
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3121076
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1617
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 42139904
86.8%
Common 6394802
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4530059
 
10.8%
i 3300515
 
7.8%
r 3283333
 
7.8%
a 3180184
 
7.5%
t 2853937
 
6.8%
o 2635467
 
6.3%
s 2190723
 
5.2%
n 2099413
 
5.0%
S 2058471
 
4.9%
l 1550002
 
3.7%
Other values (37) 14457800
34.3%
Common
ValueCountFrequency (%)
3157835
49.4%
- 3121076
48.8%
3 50862
 
0.8%
1 39053
 
0.6%
2 24359
 
0.4%
& 1617
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48534706
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4530059
 
9.3%
i 3300515
 
6.8%
r 3283333
 
6.8%
a 3180184
 
6.6%
3157835
 
6.5%
- 3121076
 
6.4%
t 2853937
 
5.9%
o 2635467
 
5.4%
s 2190723
 
4.5%
n 2099413
 
4.3%
Other values (43) 18182164
37.5%

REQUEST TYPE
Categorical

Distinct1236
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
Property Violations
224533 
Nuisance Violations
 
41386
Animal Control
 
34613
Water Leak or Pressure Problem
 
33054
Dead Animal Pick-up
 
28712
Other values (1231)
1200917 

Length

Max length80
Median length67
Mean length32.553566
Min length7

Characters and Unicode

Total characters50888223
Distinct characters73
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)< 0.1%

Sample

1st rowProp/Build/Construct-Dangerous Building-On list
2nd rowStreets / Roadways / Alleys-Crack-District 1
3rd rowProp/Build/Construct-Dangerous Building-On list
4th rowProperty Violations
5th rowParks & Recreation-Park Maintenance-Central

Common Values

ValueCountFrequency (%)
Property Violations 224533
 
14.4%
Nuisance Violations 41386
 
2.6%
Animal Control 34613
 
2.2%
Water Leak or Pressure Problem 33054
 
2.1%
Dead Animal Pick-up 28712
 
1.8%
Trash / Recycling-Trash Collection-Missed by Contractor South 28476
 
1.8%
Solid Waste Customer Service 23091
 
1.5%
Trash / Recycling-Trash Collection-Missed by Contractor North 22272
 
1.4%
Streets / Roadways / Alleys-Pothole-District 3 22042
 
1.4%
Abandoned Vehicle 19023
 
1.2%
Other values (1226) 1086013
69.5%

Length

2023-02-25T10:12:14.105230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
765661
 
11.3%
violations 297534
 
4.4%
property 272148
 
4.0%
trash 239752
 
3.5%
by 172991
 
2.5%
animal 132435
 
1.9%
water 126206
 
1.9%
or 121976
 
1.8%
contractor 119869
 
1.8%
missed 101448
 
1.5%
Other values (1269) 4453170
65.5%

Most occurring characters

ValueCountFrequency (%)
5240289
 
10.3%
e 4342352
 
8.5%
r 3473307
 
6.8%
t 3409110
 
6.7%
i 3178178
 
6.2%
o 2898784
 
5.7%
a 2854112
 
5.6%
n 2631165
 
5.2%
s 2510366
 
4.9%
l 1989500
 
3.9%
Other values (63) 18361060
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36579696
71.9%
Uppercase Letter 6621246
 
13.0%
Space Separator 5240289
 
10.3%
Dash Punctuation 1431477
 
2.8%
Other Punctuation 713489
 
1.4%
Decimal Number 213756
 
0.4%
Open Punctuation 43303
 
0.1%
Close Punctuation 42842
 
0.1%
Math Symbol 2038
 
< 0.1%
Initial Punctuation 87
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4342352
11.9%
r 3473307
9.5%
t 3409110
9.3%
i 3178178
8.7%
o 2898784
 
7.9%
a 2854112
 
7.8%
n 2631165
 
7.2%
s 2510366
 
6.9%
l 1989500
 
5.4%
c 1480628
 
4.0%
Other values (16) 7812194
21.4%
Uppercase Letter
ValueCountFrequency (%)
S 843642
12.7%
P 822834
12.4%
R 587903
8.9%
C 583764
8.8%
T 552829
 
8.3%
A 472383
 
7.1%
V 373397
 
5.6%
M 356041
 
5.4%
W 323551
 
4.9%
D 309053
 
4.7%
Other values (15) 1395849
21.1%
Decimal Number
ValueCountFrequency (%)
1 45085
21.1%
3 42714
20.0%
2 42378
19.8%
7 28431
13.3%
4 27627
12.9%
0 14649
 
6.9%
5 4530
 
2.1%
6 2921
 
1.4%
8 2813
 
1.3%
9 2608
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 702783
98.5%
& 6604
 
0.9%
, 3964
 
0.6%
' 108
 
< 0.1%
. 30
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1423974
99.5%
– 7503
 
0.5%
Space Separator
ValueCountFrequency (%)
5240289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43303
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42842
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2038
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43200942
84.9%
Common 7687281
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4342352
 
10.1%
r 3473307
 
8.0%
t 3409110
 
7.9%
i 3178178
 
7.4%
o 2898784
 
6.7%
a 2854112
 
6.6%
n 2631165
 
6.1%
s 2510366
 
5.8%
l 1989500
 
4.6%
c 1480628
 
3.4%
Other values (41) 14433440
33.4%
Common
ValueCountFrequency (%)
5240289
68.2%
- 1423974
 
18.5%
/ 702783
 
9.1%
1 45085
 
0.6%
( 43303
 
0.6%
) 42842
 
0.6%
3 42714
 
0.6%
2 42378
 
0.6%
7 28431
 
0.4%
4 27627
 
0.4%
Other values (12) 47855
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50880633
> 99.9%
Punctuation 7590
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5240289
 
10.3%
e 4342352
 
8.5%
r 3473307
 
6.8%
t 3409110
 
6.7%
i 3178178
 
6.2%
o 2898784
 
5.7%
a 2854112
 
5.6%
n 2631165
 
5.2%
s 2510366
 
4.9%
l 1989500
 
3.9%
Other values (61) 18353470
36.1%
Punctuation
ValueCountFrequency (%)
– 7503
98.9%
‘ 87
 
1.1%

CATEGORY
Categorical

Distinct84
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
Trash / Recycling
205683 
Trash
168125 
Property Violations
134094 
Animal
98921 
Streets / Roadways / Alleys
 
74919
Other values (79)
881473 

Length

Max length35
Median length30
Mean length13.94984
Min length3

Characters and Unicode

Total characters21806599
Distinct characters48
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowProperty / Buildings / Construction
2nd rowStreets / Roadways / Alleys
3rd rowProperty / Buildings / Construction
4th rowProperty / Buildings / Construction
5th rowParks & Recreation

Common Values

ValueCountFrequency (%)
Trash / Recycling 205683
 
13.2%
Trash 168125
 
10.8%
Property Violations 134094
 
8.6%
Animal 98921
 
6.3%
Streets / Roadways / Alleys 74919
 
4.8%
Trees 73966
 
4.7%
Animals / Pets 73694
 
4.7%
Property / Buildings / Construction 73234
 
4.7%
Water Leak 71347
 
4.6%
Water 56724
 
3.6%
Other values (74) 532508
34.1%

Length

2023-02-25T10:12:14.185015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
777196
21.6%
trash 373808
 
10.4%
property 232185
 
6.5%
recycling 205683
 
5.7%
violations 199740
 
5.6%
water 185164
 
5.2%
animal 98921
 
2.8%
streets 74919
 
2.1%
roadways 74919
 
2.1%
alleys 74919
 
2.1%
Other values (101) 1295445
36.1%

Most occurring characters

ValueCountFrequency (%)
2029684
 
9.3%
e 1770832
 
8.1%
r 1514568
 
6.9%
i 1482107
 
6.8%
s 1453162
 
6.7%
a 1415107
 
6.5%
t 1330280
 
6.1%
n 1154224
 
5.3%
o 1090374
 
5.0%
l 1026372
 
4.7%
Other values (38) 7539889
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16186973
74.2%
Uppercase Letter 2812746
 
12.9%
Space Separator 2029684
 
9.3%
Other Punctuation 777196
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1770832
10.9%
r 1514568
9.4%
i 1482107
9.2%
s 1453162
9.0%
a 1415107
8.7%
t 1330280
8.2%
n 1154224
 
7.1%
o 1090374
 
6.7%
l 1026372
 
6.3%
c 727972
 
4.5%
Other values (14) 3221975
19.9%
Uppercase Letter
ValueCountFrequency (%)
T 457894
16.3%
P 421154
15.0%
S 333684
11.9%
R 290911
10.3%
A 276437
9.8%
W 261172
9.3%
V 248665
8.8%
L 119789
 
4.3%
B 100690
 
3.6%
C 97569
 
3.5%
Other values (11) 204781
7.3%
Other Punctuation
ValueCountFrequency (%)
/ 719830
92.6%
& 57366
 
7.4%
Space Separator
ValueCountFrequency (%)
2029684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18999719
87.1%
Common 2806880
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1770832
 
9.3%
r 1514568
 
8.0%
i 1482107
 
7.8%
s 1453162
 
7.6%
a 1415107
 
7.4%
t 1330280
 
7.0%
n 1154224
 
6.1%
o 1090374
 
5.7%
l 1026372
 
5.4%
c 727972
 
3.8%
Other values (35) 6034721
31.8%
Common
ValueCountFrequency (%)
2029684
72.3%
/ 719830
 
25.6%
& 57366
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21806599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2029684
 
9.3%
e 1770832
 
8.1%
r 1514568
 
6.9%
i 1482107
 
6.8%
s 1453162
 
6.7%
a 1415107
 
6.5%
t 1330280
 
6.1%
n 1154224
 
5.3%
o 1090374
 
5.0%
l 1026372
 
4.7%
Other values (38) 7539889
34.6%

TYPE
Categorical

Distinct295
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
Private Property
181843 
Trash Collection
 
70001
Property Maintenance
 
56455
Street
 
48630
Pothole
 
39777
Other values (290)
1166509 

Length

Max length48
Median length29
Mean length11.899895
Min length2

Characters and Unicode

Total characters18602094
Distinct characters69
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowDangerous Building
2nd rowCrack
3rd rowDangerous Building
4th rowProperty Maintenance
5th rowPark Maintenance

Common Values

ValueCountFrequency (%)
Private Property 181843
 
11.6%
Trash Collection 70001
 
4.5%
Property Maintenance 56455
 
3.6%
Street 48630
 
3.1%
Pothole 39777
 
2.5%
Recycling 38664
 
2.5%
Investigations 36064
 
2.3%
Other 34611
 
2.2%
Services 31559
 
2.0%
Administration 30418
 
1.9%
Other values (285) 995193
63.7%

Length

2023-02-25T10:12:14.257493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
property 246467
 
9.1%
private 213828
 
7.9%
118647
 
4.4%
street 99068
 
3.7%
trash 70159
 
2.6%
collection 70001
 
2.6%
maintenance 65340
 
2.4%
animal 52113
 
1.9%
stray 47867
 
1.8%
pothole 39777
 
1.5%
Other values (343) 1683117
62.2%

Most occurring characters

ValueCountFrequency (%)
e 1934335
 
10.4%
r 1626910
 
8.7%
t 1536231
 
8.3%
a 1346391
 
7.2%
i 1251603
 
6.7%
1143169
 
6.1%
n 1133790
 
6.1%
o 1009491
 
5.4%
l 663892
 
3.6%
P 578906
 
3.1%
Other values (59) 6377376
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14743571
79.3%
Uppercase Letter 2509188
 
13.5%
Space Separator 1143169
 
6.1%
Other Punctuation 125515
 
0.7%
Decimal Number 54301
 
0.3%
Dash Punctuation 13999
 
0.1%
Open Punctuation 6102
 
< 0.1%
Close Punctuation 6102
 
< 0.1%
Initial Punctuation 147
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1934335
13.1%
r 1626910
11.0%
t 1536231
10.4%
a 1346391
9.1%
i 1251603
 
8.5%
n 1133790
 
7.7%
o 1009491
 
6.8%
l 663892
 
4.5%
c 562616
 
3.8%
y 499008
 
3.4%
Other values (16) 3179304
21.6%
Uppercase Letter
ValueCountFrequency (%)
P 578906
23.1%
S 289650
11.5%
C 240537
9.6%
R 183614
 
7.3%
A 162665
 
6.5%
B 147822
 
5.9%
T 145769
 
5.8%
D 118884
 
4.7%
L 109082
 
4.3%
M 108032
 
4.3%
Other values (15) 424227
16.9%
Decimal Number
ValueCountFrequency (%)
1 14948
27.5%
2 11371
20.9%
0 8742
16.1%
3 3140
 
5.8%
6 2923
 
5.4%
8 2812
 
5.2%
4 2647
 
4.9%
7 2619
 
4.8%
9 2608
 
4.8%
5 2491
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/ 116109
92.5%
& 9373
 
7.5%
. 33
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1143169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13999
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6102
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17252759
92.7%
Common 1349335
 
7.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1934335
 
11.2%
r 1626910
 
9.4%
t 1536231
 
8.9%
a 1346391
 
7.8%
i 1251603
 
7.3%
n 1133790
 
6.6%
o 1009491
 
5.9%
l 663892
 
3.8%
P 578906
 
3.4%
c 562616
 
3.3%
Other values (41) 5608594
32.5%
Common
ValueCountFrequency (%)
1143169
84.7%
/ 116109
 
8.6%
1 14948
 
1.1%
- 13999
 
1.0%
2 11371
 
0.8%
& 9373
 
0.7%
0 8742
 
0.6%
( 6102
 
0.5%
) 6102
 
0.5%
3 3140
 
0.2%
Other values (8) 16280
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18601947
> 99.9%
Punctuation 147
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1934335
 
10.4%
r 1626910
 
8.7%
t 1536231
 
8.3%
a 1346391
 
7.2%
i 1251603
 
6.7%
1143169
 
6.1%
n 1133790
 
6.1%
o 1009491
 
5.4%
l 663892
 
3.6%
P 578906
 
3.1%
Other values (58) 6377229
34.3%
Punctuation
ValueCountFrequency (%)
‘ 147
100.0%

DETAIL
Categorical

Distinct574
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
All
426673 
Missed
 
49518
Missed by Contractor North
 
39989
Missed by Contractor South
 
39955
Non Emergency
 
34611
Other values (569)
972469 

Length

Max length48
Median length31
Mean length10.467135
Min length3

Characters and Unicode

Total characters16362382
Distinct characters66
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)< 0.1%

Sample

1st rowStandard
2nd rowDistrict 1
3rd rowStandard
4th rowOther Property Issue
5th rowCentral

Common Values

ValueCountFrequency (%)
All 426673
27.3%
Missed 49518
 
3.2%
Missed by Contractor North 39989
 
2.6%
Missed by Contractor South 39955
 
2.6%
Non Emergency 34611
 
2.2%
*Select one 32305
 
2.1%
District 3 31905
 
2.0%
Dead 30393
 
1.9%
Missed by City 27268
 
1.7%
Other Property Issue 26124
 
1.7%
Other values (564) 824474
52.7%

Length

2023-02-25T10:12:14.328963image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
all 428758
 
14.3%
missed 172087
 
5.8%
135089
 
4.5%
by 107464
 
3.6%
district 107235
 
3.6%
contractor 89601
 
3.0%
property 70100
 
2.3%
south 69653
 
2.3%
north 60495
 
2.0%
one 57947
 
1.9%
Other values (600) 1693151
56.6%

Most occurring characters

ValueCountFrequency (%)
e 1505379
 
9.2%
1428365
 
8.7%
t 1310932
 
8.0%
r 1212748
 
7.4%
l 1087247
 
6.6%
i 896135
 
5.5%
o 845654
 
5.2%
s 787339
 
4.8%
n 708151
 
4.3%
a 643131
 
3.9%
Other values (56) 5937301
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11901213
72.7%
Uppercase Letter 2711940
 
16.6%
Space Separator 1428365
 
8.7%
Dash Punctuation 114893
 
0.7%
Other Punctuation 108326
 
0.7%
Decimal Number 78896
 
0.5%
Open Punctuation 8339
 
0.1%
Close Punctuation 8339
 
0.1%
Math Symbol 2038
 
< 0.1%
Initial Punctuation 33
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1505379
12.6%
t 1310932
11.0%
r 1212748
10.2%
l 1087247
9.1%
i 896135
 
7.5%
o 845654
 
7.1%
s 787339
 
6.6%
n 708151
 
6.0%
a 643131
 
5.4%
c 431294
 
3.6%
Other values (16) 2473203
20.8%
Uppercase Letter
ValueCountFrequency (%)
A 510716
18.8%
S 295407
10.9%
M 234827
8.7%
C 234346
8.6%
D 189901
 
7.0%
P 175668
 
6.5%
N 159626
 
5.9%
L 151890
 
5.6%
O 134016
 
4.9%
T 120206
 
4.4%
Other values (15) 505337
18.6%
Decimal Number
ValueCountFrequency (%)
3 31985
40.5%
1 22084
28.0%
2 20851
26.4%
5 2038
 
2.6%
4 1938
 
2.5%
Other Punctuation
ValueCountFrequency (%)
/ 62947
58.1%
* 45286
41.8%
' 64
 
0.1%
. 29
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1428365
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114893
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8339
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8339
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2038
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14613153
89.3%
Common 1749229
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1505379
 
10.3%
t 1310932
 
9.0%
r 1212748
 
8.3%
l 1087247
 
7.4%
i 896135
 
6.1%
o 845654
 
5.8%
s 787339
 
5.4%
n 708151
 
4.8%
a 643131
 
4.4%
A 510716
 
3.5%
Other values (41) 5105721
34.9%
Common
ValueCountFrequency (%)
1428365
81.7%
- 114893
 
6.6%
/ 62947
 
3.6%
* 45286
 
2.6%
3 31985
 
1.8%
1 22084
 
1.3%
2 20851
 
1.2%
( 8339
 
0.5%
) 8339
 
0.5%
5 2038
 
0.1%
Other values (5) 4102
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16362349
> 99.9%
Punctuation 33
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1505379
 
9.2%
1428365
 
8.7%
t 1310932
 
8.0%
r 1212748
 
7.4%
l 1087247
 
6.6%
i 896135
 
5.5%
o 845654
 
5.2%
s 787339
 
4.8%
n 708151
 
4.3%
a 643131
 
3.9%
Other values (55) 5937268
36.3%
Punctuation
ValueCountFrequency (%)
‘ 33
100.0%

CREATION DATE
Categorical

Distinct5229
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
01/22/2019
 
2313
01/24/2019
 
2130
01/23/2019
 
1816
01/13/2010
 
1794
01/14/2010
 
1762
Other values (5224)
1553400 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters15632150
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)< 0.1%

Sample

1st row06/24/2019
2nd row12/22/2019
3rd row01/19/2021
4th row11/25/2020
5th row04/18/2020

Common Values

ValueCountFrequency (%)
01/22/2019 2313
 
0.1%
01/24/2019 2130
 
0.1%
01/23/2019 1816
 
0.1%
01/13/2010 1794
 
0.1%
01/14/2010 1762
 
0.1%
01/17/2019 1656
 
0.1%
11/28/2018 1646
 
0.1%
11/27/2018 1453
 
0.1%
01/25/2019 1448
 
0.1%
11/29/2018 1424
 
0.1%
Other values (5219) 1545773
98.9%

Length

2023-02-25T10:12:14.390453image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
01/22/2019 2313
 
0.1%
01/24/2019 2130
 
0.1%
01/23/2019 1816
 
0.1%
01/13/2010 1794
 
0.1%
01/14/2010 1762
 
0.1%
01/17/2019 1656
 
0.1%
11/28/2018 1646
 
0.1%
11/27/2018 1453
 
0.1%
01/25/2019 1448
 
0.1%
11/29/2018 1424
 
0.1%
Other values (5219) 1545773
98.9%

Most occurring characters

ValueCountFrequency (%)
0 4095304
26.2%
/ 3126430
20.0%
2 2700418
17.3%
1 2466958
15.8%
9 566063
 
3.6%
8 560925
 
3.6%
7 488082
 
3.1%
3 450259
 
2.9%
6 407050
 
2.6%
5 397145
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12505720
80.0%
Other Punctuation 3126430
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4095304
32.7%
2 2700418
21.6%
1 2466958
19.7%
9 566063
 
4.5%
8 560925
 
4.5%
7 488082
 
3.9%
3 450259
 
3.6%
6 407050
 
3.3%
5 397145
 
3.2%
4 373516
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/ 3126430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15632150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4095304
26.2%
/ 3126430
20.0%
2 2700418
17.3%
1 2466958
15.8%
9 566063
 
3.6%
8 560925
 
3.6%
7 488082
 
3.1%
3 450259
 
2.9%
6 407050
 
2.6%
5 397145
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15632150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4095304
26.2%
/ 3126430
20.0%
2 2700418
17.3%
1 2466958
15.8%
9 566063
 
3.6%
8 560925
 
3.6%
7 488082
 
3.1%
3 450259
 
2.9%
6 407050
 
2.6%
5 397145
 
2.5%

CREATION TIME
Categorical

Distinct1440
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
11:01 AM
 
2878
10:41 AM
 
2849
10:43 AM
 
2826
10:48 AM
 
2820
10:58 AM
 
2809
Other values (1435)
1549033 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters12505720
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07:40 AM
2nd row07:56 PM
3rd row02:43 PM
4th row09:19 AM
5th row05:10 PM

Common Values

ValueCountFrequency (%)
11:01 AM 2878
 
0.2%
10:41 AM 2849
 
0.2%
10:43 AM 2826
 
0.2%
10:48 AM 2820
 
0.2%
10:58 AM 2809
 
0.2%
09:48 AM 2801
 
0.2%
10:55 AM 2788
 
0.2%
10:54 AM 2784
 
0.2%
10:50 AM 2782
 
0.2%
10:32 AM 2779
 
0.2%
Other values (1430) 1535099
98.2%

Length

2023-02-25T10:12:14.445262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 879025
28.1%
am 684190
21.9%
11:01 2983
 
0.1%
10:41 2980
 
0.1%
09:42 2940
 
0.1%
09:45 2936
 
0.1%
10:43 2936
 
0.1%
10:48 2930
 
0.1%
09:48 2925
 
0.1%
09:41 2924
 
0.1%
Other values (712) 1539661
49.2%

Most occurring characters

ValueCountFrequency (%)
0 1682522
13.5%
: 1563215
12.5%
1563215
12.5%
M 1563215
12.5%
1 1182599
9.5%
P 879025
7.0%
2 699543
5.6%
A 684190
5.5%
3 562416
 
4.5%
4 545820
 
4.4%
Other values (5) 1579960
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6252860
50.0%
Uppercase Letter 3126430
25.0%
Other Punctuation 1563215
 
12.5%
Space Separator 1563215
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1682522
26.9%
1 1182599
18.9%
2 699543
11.2%
3 562416
 
9.0%
4 545820
 
8.7%
5 493755
 
7.9%
9 323319
 
5.2%
8 304275
 
4.9%
7 230814
 
3.7%
6 227797
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
M 1563215
50.0%
P 879025
28.1%
A 684190
21.9%
Other Punctuation
ValueCountFrequency (%)
: 1563215
100.0%
Space Separator
ValueCountFrequency (%)
1563215
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9379290
75.0%
Latin 3126430
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1682522
17.9%
: 1563215
16.7%
1563215
16.7%
1 1182599
12.6%
2 699543
7.5%
3 562416
 
6.0%
4 545820
 
5.8%
5 493755
 
5.3%
9 323319
 
3.4%
8 304275
 
3.2%
Other values (2) 458611
 
4.9%
Latin
ValueCountFrequency (%)
M 1563215
50.0%
P 879025
28.1%
A 684190
21.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12505720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1682522
13.5%
: 1563215
12.5%
1563215
12.5%
M 1563215
12.5%
1 1182599
9.5%
P 879025
7.0%
2 699543
5.6%
A 684190
5.5%
3 562416
 
4.5%
4 545820
 
4.4%
Other values (5) 1579960
12.6%

CREATION MONTH
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2869618
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:14.497280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3485904
Coefficient of variation (CV)0.53262458
Kurtosis-1.1016162
Mean6.2869618
Median Absolute Deviation (MAD)3
Skewness0.063491463
Sum9827873
Variance11.213058
MonotonicityNot monotonic
2023-02-25T10:12:14.549064image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 152005
9.7%
6 150000
9.6%
1 143890
9.2%
8 141492
9.1%
7 140286
9.0%
4 131977
8.4%
3 126558
8.1%
9 125359
8.0%
2 121288
7.8%
10 116238
7.4%
Other values (2) 214122
13.7%
ValueCountFrequency (%)
1 143890
9.2%
2 121288
7.8%
3 126558
8.1%
4 131977
8.4%
5 152005
9.7%
6 150000
9.6%
7 140286
9.0%
8 141492
9.1%
9 125359
8.0%
10 116238
7.4%
ValueCountFrequency (%)
12 113909
7.3%
11 100213
6.4%
10 116238
7.4%
9 125359
8.0%
8 141492
9.1%
7 140286
9.0%
6 150000
9.6%
5 152005
9.7%
4 131977
8.4%
3 126558
8.1%

CREATION YEAR
Real number (ℝ)

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.9035
Minimum2006
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:14.601915image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2007
Q12010
median2014
Q32018
95-th percentile2020
Maximum2021
Range15
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.2488245
Coefficient of variation (CV)0.0021097458
Kurtosis-1.3473795
Mean2013.9035
Median Absolute Deviation (MAD)4
Skewness-0.074539278
Sum3.1481642 × 109
Variance18.05251
MonotonicityNot monotonic
2023-02-25T10:12:14.655383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2019 166021
10.6%
2008 137894
 
8.8%
2020 125906
 
8.1%
2018 124280
 
8.0%
2009 119269
 
7.6%
2010 110276
 
7.1%
2017 109811
 
7.0%
2016 103955
 
6.7%
2015 96941
 
6.2%
2011 96113
 
6.1%
Other values (6) 372749
23.8%
ValueCountFrequency (%)
2006 1
 
< 0.1%
2007 83075
5.3%
2008 137894
8.8%
2009 119269
7.6%
2010 110276
7.1%
2011 96113
6.1%
2012 90199
5.8%
2013 90462
5.8%
2014 89329
5.7%
2015 96941
6.2%
ValueCountFrequency (%)
2021 19683
 
1.3%
2020 125906
8.1%
2019 166021
10.6%
2018 124280
8.0%
2017 109811
7.0%
2016 103955
6.7%
2015 96941
6.2%
2014 89329
5.7%
2013 90462
5.8%
2012 90199
5.8%

STATUS
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
RESOL
1535389 
CANC
 
13818
OPEN
 
12657
DUP
 
1301
ASSIG
 
45

Length

Max length5
Median length5
Mean length4.981396
Min length3

Characters and Unicode

Total characters7786993
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRESOL
2nd rowRESOL
3rd rowRESOL
4th rowRESOL
5th rowRESOL

Common Values

ValueCountFrequency (%)
RESOL 1535389
98.2%
CANC 13818
 
0.9%
OPEN 12657
 
0.8%
DUP 1301
 
0.1%
ASSIG 45
 
< 0.1%
FAIL 5
 
< 0.1%

Length

2023-02-25T10:12:14.721547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-25T10:12:14.798294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
resol 1535389
98.2%
canc 13818
 
0.9%
open 12657
 
0.8%
dup 1301
 
0.1%
assig 45
 
< 0.1%
fail 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
E 1548046
19.9%
O 1548046
19.9%
S 1535479
19.7%
L 1535394
19.7%
R 1535389
19.7%
C 27636
 
0.4%
N 26475
 
0.3%
P 13958
 
0.2%
A 13868
 
0.2%
D 1301
 
< 0.1%
Other values (4) 1401
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7786993
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1548046
19.9%
O 1548046
19.9%
S 1535479
19.7%
L 1535394
19.7%
R 1535389
19.7%
C 27636
 
0.4%
N 26475
 
0.3%
P 13958
 
0.2%
A 13868
 
0.2%
D 1301
 
< 0.1%
Other values (4) 1401
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 7786993
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1548046
19.9%
O 1548046
19.9%
S 1535479
19.7%
L 1535394
19.7%
R 1535389
19.7%
C 27636
 
0.4%
N 26475
 
0.3%
P 13958
 
0.2%
A 13868
 
0.2%
D 1301
 
< 0.1%
Other values (4) 1401
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7786993
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 1548046
19.9%
O 1548046
19.9%
S 1535479
19.7%
L 1535394
19.7%
R 1535389
19.7%
C 27636
 
0.4%
N 26475
 
0.3%
P 13958
 
0.2%
A 13868
 
0.2%
D 1301
 
< 0.1%
Other values (4) 1401
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing23
Missing (%)< 0.1%
Memory size3.0 MiB
False
1079493 
True
483699 
(Missing)
 
23
ValueCountFrequency (%)
False 1079493
69.1%
True 483699
30.9%
(Missing) 23
 
< 0.1%
2023-02-25T10:12:14.860090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

CLOSED DATE
Categorical

Distinct4995
Distinct (%)0.3%
Missing12702
Missing (%)0.8%
Memory size11.9 MiB
09/30/2019
 
13841
05/05/2014
 
4595
03/25/2019
 
3471
02/23/2010
 
3313
12/03/2018
 
3281
Other values (4990)
1522012 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters15505130
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)< 0.1%

Sample

1st row11/19/2021
2nd row06/26/2020
3rd row11/15/2021
4th row04/26/2021
5th row04/30/2020

Common Values

ValueCountFrequency (%)
09/30/2019 13841
 
0.9%
05/05/2014 4595
 
0.3%
03/25/2019 3471
 
0.2%
02/23/2010 3313
 
0.2%
12/03/2018 3281
 
0.2%
04/05/2019 2863
 
0.2%
07/29/2009 2764
 
0.2%
02/14/2019 1988
 
0.1%
02/13/2019 1838
 
0.1%
02/21/2019 1794
 
0.1%
Other values (4985) 1510765
96.6%
(Missing) 12702
 
0.8%

Length

2023-02-25T10:12:14.912107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
09/30/2019 13841
 
0.9%
05/05/2014 4595
 
0.3%
03/25/2019 3471
 
0.2%
02/23/2010 3313
 
0.2%
12/03/2018 3281
 
0.2%
04/05/2019 2863
 
0.2%
07/29/2009 2764
 
0.2%
02/14/2019 1988
 
0.1%
02/13/2019 1838
 
0.1%
02/21/2019 1794
 
0.1%
Other values (4985) 1510765
97.4%

Most occurring characters

ValueCountFrequency (%)
0 4033809
26.0%
/ 3101026
20.0%
2 2686065
17.3%
1 2487899
16.0%
9 588607
 
3.8%
8 528897
 
3.4%
7 474108
 
3.1%
3 467330
 
3.0%
6 397554
 
2.6%
5 379896
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12404104
80.0%
Other Punctuation 3101026
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4033809
32.5%
2 2686065
21.7%
1 2487899
20.1%
9 588607
 
4.7%
8 528897
 
4.3%
7 474108
 
3.8%
3 467330
 
3.8%
6 397554
 
3.2%
5 379896
 
3.1%
4 359939
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 3101026
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15505130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4033809
26.0%
/ 3101026
20.0%
2 2686065
17.3%
1 2487899
16.0%
9 588607
 
3.8%
8 528897
 
3.4%
7 474108
 
3.1%
3 467330
 
3.0%
6 397554
 
2.6%
5 379896
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15505130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4033809
26.0%
/ 3101026
20.0%
2 2686065
17.3%
1 2487899
16.0%
9 588607
 
3.8%
8 528897
 
3.4%
7 474108
 
3.1%
3 467330
 
3.0%
6 397554
 
2.6%
5 379896
 
2.5%

CLOSED MONTH
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing26515
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean6.4092647
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:14.964347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3998366
Coefficient of variation (CV)0.53045659
Kurtosis-1.1648866
Mean6.4092647
Median Absolute Deviation (MAD)3
Skewness0.025655982
Sum9849117
Variance11.558889
MonotonicityNot monotonic
2023-02-25T10:12:15.016472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
6 139557
8.9%
7 139100
8.9%
5 133823
8.6%
8 133050
8.5%
3 132449
8.5%
1 129537
8.3%
2 128834
8.2%
10 127722
8.2%
9 124401
8.0%
12 122014
7.8%
Other values (2) 226213
14.5%
ValueCountFrequency (%)
1 129537
8.3%
2 128834
8.2%
3 132449
8.5%
4 118476
7.6%
5 133823
8.6%
6 139557
8.9%
7 139100
8.9%
8 133050
8.5%
9 124401
8.0%
10 127722
8.2%
ValueCountFrequency (%)
12 122014
7.8%
11 107737
6.9%
10 127722
8.2%
9 124401
8.0%
8 133050
8.5%
7 139100
8.9%
6 139557
8.9%
5 133823
8.6%
4 118476
7.6%
3 132449
8.5%

CLOSED YEAR
Real number (ℝ)

Distinct16
Distinct (%)< 0.1%
Missing26515
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean2014.0239
Minimum2007
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:15.069401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2008
Q12010
median2014
Q32018
95-th percentile2020
Maximum2022
Range15
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.2253652
Coefficient of variation (CV)0.0020979717
Kurtosis-1.3244347
Mean2014.0239
Median Absolute Deviation (MAD)4
Skewness-0.098468027
Sum3.0949505 × 109
Variance17.853711
MonotonicityNot monotonic
2023-02-25T10:12:15.122892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2019 165353
10.6%
2018 123273
 
7.9%
2008 123016
 
7.9%
2020 122641
 
7.8%
2009 119223
 
7.6%
2017 111686
 
7.1%
2016 104931
 
6.7%
2011 101907
 
6.5%
2010 101188
 
6.5%
2015 92506
 
5.9%
Other values (6) 370976
23.7%
ValueCountFrequency (%)
2007 75817
4.9%
2008 123016
7.9%
2009 119223
7.6%
2010 101188
6.5%
2011 101907
6.5%
2012 88661
5.7%
2013 88566
5.7%
2014 91518
5.9%
2015 92506
5.9%
2016 104931
6.7%
ValueCountFrequency (%)
2022 9
 
< 0.1%
2021 26405
 
1.7%
2020 122641
7.8%
2019 165353
10.6%
2018 123273
7.9%
2017 111686
7.1%
2016 104931
6.7%
2015 92506
5.9%
2014 91518
5.9%
2013 88566
5.7%

DAYS TO CLOSE
Real number (ℝ)

MISSING  ZEROS 

Distinct2748
Distinct (%)0.2%
Missing26515
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean51.533404
Minimum-21
Maximum4525
Zeros150614
Zeros (%)9.6%
Negative29
Negative (%)< 0.1%
Memory size11.9 MiB
2023-02-25T10:12:15.189974image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-21
5-th percentile0
Q11
median4
Q323
95-th percentile261
Maximum4525
Range4546
Interquartile range (IQR)22

Descriptive statistics

Standard deviation169.57318
Coefficient of variation (CV)3.2905488
Kurtosis77.017163
Mean51.533404
Median Absolute Deviation (MAD)3
Skewness7.3881016
Sum79191382
Variance28755.063
MonotonicityNot monotonic
2023-02-25T10:12:15.261320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 322471
20.6%
0 150614
 
9.6%
2 120416
 
7.7%
3 103139
 
6.6%
4 77824
 
5.0%
5 57503
 
3.7%
6 49736
 
3.2%
7 44990
 
2.9%
8 31128
 
2.0%
9 20513
 
1.3%
Other values (2738) 558366
35.7%
(Missing) 26515
 
1.7%
ValueCountFrequency (%)
-21 17
 
< 0.1%
-20 2
 
< 0.1%
-19 8
 
< 0.1%
-18 1
 
< 0.1%
-1 1
 
< 0.1%
0 150614
9.6%
1 322471
20.6%
2 120416
 
7.7%
3 103139
 
6.6%
4 77824
 
5.0%
ValueCountFrequency (%)
4525 1
< 0.1%
4471 1
< 0.1%
4396 1
< 0.1%
4188 1
< 0.1%
4183 1
< 0.1%
4175 1
< 0.1%
4160 1
< 0.1%
4157 1
< 0.1%
4135 1
< 0.1%
4132 1
< 0.1%

STREET ADDRESS
Categorical

Distinct277728
Distinct (%)17.8%
Missing24
Missing (%)< 0.1%
Memory size11.9 MiB
414 E 12TH ST
 
3351
414 E 12th St
 
2421
4800 E 63rd St
 
2330
415 E 12th St
 
1246
415 E 12th st
 
570
Other values (277723)
1553273 

Length

Max length39
Median length37
Mean length15.80865
Min length4

Characters and Unicode

Total characters24711939
Distinct characters75
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67349 ?
Unique (%)4.3%

Sample

1st row2317 E 50th St
2nd row10329 N Forest Ave
3rd row2623 E 10th St
4th row2474 Chelsea Ave
5th row400 W 31st St

Common Values

ValueCountFrequency (%)
414 E 12TH ST 3351
 
0.2%
414 E 12th St 2421
 
0.2%
4800 E 63rd St 2330
 
0.1%
415 E 12th St 1246
 
0.1%
415 E 12th st 570
 
< 0.1%
400 W 31st St 430
 
< 0.1%
5100 Wornall Rd 323
 
< 0.1%
2400 Troost Ave 290
 
< 0.1%
4900 Raytown Rd 282
 
< 0.1%
7750 E Front St 269
 
< 0.1%
Other values (277718) 1551679
99.3%

Length

2023-02-25T10:12:15.348642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ave 602207
 
10.9%
st 476456
 
8.6%
e 327586
 
5.9%
n 180177
 
3.3%
ter 156915
 
2.8%
rd 131274
 
2.4%
ne 112479
 
2.0%
w 70394
 
1.3%
blvd 64833
 
1.2%
nw 64756
 
1.2%
Other values (12145) 3334294
60.4%

Most occurring characters

ValueCountFrequency (%)
3958210
 
16.0%
1 1284556
 
5.2%
0 1173280
 
4.7%
E 1116467
 
4.5%
e 909295
 
3.7%
A 892797
 
3.6%
2 785798
 
3.2%
t 762941
 
3.1%
T 726450
 
2.9%
3 717530
 
2.9%
Other values (65) 12384615
50.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7637289
30.9%
Decimal Number 7183875
29.1%
Lowercase Letter 5925190
24.0%
Space Separator 3958210
16.0%
Dash Punctuation 5688
 
< 0.1%
Other Punctuation 1677
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1116467
14.6%
A 892797
11.7%
T 726450
 
9.5%
S 694753
 
9.1%
N 661679
 
8.7%
R 501664
 
6.6%
V 331386
 
4.3%
W 291712
 
3.8%
L 290404
 
3.8%
O 286483
 
3.8%
Other values (16) 1843494
24.1%
Lowercase Letter
ValueCountFrequency (%)
e 909295
15.3%
t 762941
12.9%
r 482556
8.1%
v 427188
 
7.2%
n 420855
 
7.1%
a 372413
 
6.3%
o 364188
 
6.1%
l 354868
 
6.0%
d 338821
 
5.7%
h 306003
 
5.2%
Other values (16) 1186062
20.0%
Decimal Number
ValueCountFrequency (%)
1 1284556
17.9%
0 1173280
16.3%
2 785798
10.9%
3 717530
10.0%
4 714711
9.9%
5 619841
8.6%
6 496732
 
6.9%
7 496633
 
6.9%
8 477639
 
6.6%
9 417155
 
5.8%
Other Punctuation
ValueCountFrequency (%)
' 1342
80.0%
, 100
 
6.0%
. 70
 
4.2%
/ 70
 
4.2%
# 68
 
4.1%
& 13
 
0.8%
" 10
 
0.6%
: 3
 
0.2%
% 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3958210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5688
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13562479
54.9%
Common 11149460
45.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1116467
 
8.2%
e 909295
 
6.7%
A 892797
 
6.6%
t 762941
 
5.6%
T 726450
 
5.4%
S 694753
 
5.1%
N 661679
 
4.9%
R 501664
 
3.7%
r 482556
 
3.6%
v 427188
 
3.1%
Other values (42) 6386689
47.1%
Common
ValueCountFrequency (%)
3958210
35.5%
1 1284556
 
11.5%
0 1173280
 
10.5%
2 785798
 
7.0%
3 717530
 
6.4%
4 714711
 
6.4%
5 619841
 
5.6%
6 496732
 
4.5%
7 496633
 
4.5%
8 477639
 
4.3%
Other values (13) 424530
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24711939
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3958210
 
16.0%
1 1284556
 
5.2%
0 1173280
 
4.7%
E 1116467
 
4.5%
e 909295
 
3.7%
A 892797
 
3.6%
2 785798
 
3.2%
t 762941
 
3.1%
T 726450
 
2.9%
3 717530
 
2.9%
Other values (65) 12384615
50.1%
Distinct307249
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
414 E 12th St64106 (39.100387, -94.577919)
 
2422
414 E 12TH ST64106 (39.100387, -94.577919)
 
2414
4800 E 63rd St64130 (39.014493, -94.529933)
 
2330
415 E 12th St64106 (39.099123, -94.577983)
 
1246
414 E 12TH ST64106 (35.797519, -103.890579)
 
963
Other values (307244)
1553840 

Length

Max length69
Median length66
Mean length44.602594
Min length19

Characters and Unicode

Total characters69723444
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84541 ?
Unique (%)5.4%

Sample

1st row2317 E 50th St64130 (39.035489, -94.557309)
2nd row10329 N Forest Ave64155 (39.28196, -94.564453)
3rd row2623 E 10th St64127 (39.101272, -94.549951)
4th row2474 Chelsea Ave64127 (39.079895, -94.526959)
5th row400 W 31st St64108 (39.074934, -94.591904)

Common Values

ValueCountFrequency (%)
414 E 12th St64106 (39.100387, -94.577919) 2422
 
0.2%
414 E 12TH ST64106 (39.100387, -94.577919) 2414
 
0.2%
4800 E 63rd St64130 (39.014493, -94.529933) 2330
 
0.1%
415 E 12th St64106 (39.099123, -94.577983) 1246
 
0.1%
414 E 12TH ST64106 (35.797519, -103.890579) 963
 
0.1%
415 E 12th st64106 (35.797519, -103.890579) 570
 
< 0.1%
400 W 31st St64108 (39.074934, -94.591904) 430
 
< 0.1%
5100 Wornall Rd64112 (39.031378, -94.59448) 323
 
< 0.1%
7750 E Front St64120 (39.136326, -94.490605) 260
 
< 0.1%
2400 Troost Ave64108 (39.083166, -94.572049) 259
 
< 0.1%
Other values (307239) 1551998
99.3%

Length

2023-02-25T10:12:15.439801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
e 327581
 
3.8%
n 180180
 
2.1%
ne 112478
 
1.3%
ave64130 85500
 
1.0%
w 70398
 
0.8%
nw 64756
 
0.7%
ave64127 60184
 
0.7%
ave64128 46863
 
0.5%
103.890579 40610
 
0.5%
35.797519 40597
 
0.5%
Other values (296654) 7617276
88.1%

Most occurring characters

ValueCountFrequency (%)
4 5770240
 
8.3%
5514815
 
7.9%
9 5341801
 
7.7%
1 5255076
 
7.5%
3 4454744
 
6.4%
6 3830032
 
5.5%
5 3688003
 
5.3%
0 3456592
 
5.0%
. 3126428
 
4.5%
2 2886725
 
4.1%
Other values (63) 26398988
37.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39699460
56.9%
Uppercase Letter 7629706
 
10.9%
Lowercase Letter 5925053
 
8.5%
Space Separator 5514815
 
7.9%
Other Punctuation 4691127
 
6.7%
Dash Punctuation 1568457
 
2.2%
Control 1568393
 
2.2%
Open Punctuation 1563219
 
2.2%
Close Punctuation 1563214
 
2.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1115885
14.6%
A 892378
11.7%
T 725629
 
9.5%
S 694142
 
9.1%
N 661564
 
8.7%
R 501575
 
6.6%
V 331377
 
4.3%
W 291634
 
3.8%
L 289072
 
3.8%
O 286424
 
3.8%
Other values (16) 1840026
24.1%
Lowercase Letter
ValueCountFrequency (%)
e 909283
15.3%
t 762909
12.9%
r 482551
8.1%
v 427187
 
7.2%
n 420848
 
7.1%
a 372405
 
6.3%
o 364182
 
6.1%
l 354864
 
6.0%
d 338815
 
5.7%
h 305998
 
5.2%
Other values (16) 1186011
20.0%
Decimal Number
ValueCountFrequency (%)
4 5770240
14.5%
9 5341801
13.5%
1 5255076
13.2%
3 4454744
11.2%
6 3830032
9.6%
5 3688003
9.3%
0 3456592
8.7%
2 2886725
7.3%
8 2653764
6.7%
7 2362483
6.0%
Other Punctuation
ValueCountFrequency (%)
. 3126428
66.6%
, 1563343
33.3%
' 1342
 
< 0.1%
& 11
 
< 0.1%
# 2
 
< 0.1%
% 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5514815
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1568457
100.0%
Control
ValueCountFrequency (%)
1568393
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1563219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1563214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56168685
80.6%
Latin 13554759
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1115885
 
8.2%
e 909283
 
6.7%
A 892378
 
6.6%
t 762909
 
5.6%
T 725629
 
5.4%
S 694142
 
5.1%
N 661564
 
4.9%
R 501575
 
3.7%
r 482551
 
3.6%
v 427187
 
3.2%
Other values (42) 6381656
47.1%
Common
ValueCountFrequency (%)
4 5770240
10.3%
5514815
9.8%
9 5341801
9.5%
1 5255076
9.4%
3 4454744
 
7.9%
6 3830032
 
6.8%
5 3688003
 
6.6%
0 3456592
 
6.2%
. 3126428
 
5.6%
2 2886725
 
5.1%
Other values (11) 12844229
22.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69723444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 5770240
 
8.3%
5514815
 
7.9%
9 5341801
 
7.7%
1 5255076
 
7.5%
3 4454744
 
6.4%
6 3830032
 
5.5%
5 3688003
 
5.3%
0 3456592
 
5.0%
. 3126428
 
4.5%
2 2886725
 
4.1%
Other values (63) 26398988
37.9%

ZIP CODE
Real number (ℝ)

Distinct65
Distinct (%)< 0.1%
Missing826
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean64126.843
Minimum4114
Maximum66203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:15.513440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4114
5-th percentile64109
Q164116
median64128
Q364133
95-th percentile64155
Maximum66203
Range62089
Interquartile range (IQR)17

Descriptive statistics

Standard deviation68.122948
Coefficient of variation (CV)0.0010623156
Kurtosis721225.59
Mean64126.843
Median Absolute Deviation (MAD)9
Skewness-832.06849
Sum1.0019107 × 1011
Variance4640.7361
MonotonicityNot monotonic
2023-02-25T10:12:15.582771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64130 133154
 
8.5%
64127 90867
 
5.8%
64114 83166
 
5.3%
64134 77097
 
4.9%
64131 76437
 
4.9%
64132 76361
 
4.9%
64128 73073
 
4.7%
64110 64771
 
4.1%
64119 57224
 
3.7%
64111 50195
 
3.2%
Other values (55) 780044
49.9%
ValueCountFrequency (%)
4114 1
 
< 0.1%
6152 1
 
< 0.1%
63130 1
 
< 0.1%
64012 39
 
< 0.1%
64028 22
 
< 0.1%
64030 27
 
< 0.1%
64052 47
 
< 0.1%
64053 115
< 0.1%
64055 28
 
< 0.1%
64068 280
< 0.1%
ValueCountFrequency (%)
66203 1
 
< 0.1%
64444 15
 
< 0.1%
64167 194
 
< 0.1%
64166 460
 
< 0.1%
64165 486
 
< 0.1%
64164 522
 
< 0.1%
64163 1160
 
0.1%
64161 1936
 
0.1%
64160 89
 
< 0.1%
64158 6892
0.4%

NEIGHBORHOOD
Categorical

HIGH CARDINALITY  MISSING 

Distinct250
Distinct (%)< 0.1%
Missing46106
Missing (%)2.9%
Memory size11.9 MiB
Shoal Creek
 
55839
Blue Hills
 
31462
East Community Team South
 
21706
Scarritt Point
 
21295
South Indian Mound
 
20710
Other values (245)
1366097 

Length

Max length42
Median length29
Mean length14.972397
Min length2

Characters and Unicode

Total characters22714758
Distinct characters60
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBlue Hills
2nd rowNew Mark
3rd rowIndependence Plaza
4th rowEast Community Team South
5th rowWestside South

Common Values

ValueCountFrequency (%)
Shoal Creek 55839
 
3.6%
Blue Hills 31462
 
2.0%
East Community Team South 21706
 
1.4%
Scarritt Point 21295
 
1.4%
South Indian Mound 20710
 
1.3%
Lykins 20441
 
1.3%
Tower Homes 20031
 
1.3%
CBD Downtown 18486
 
1.2%
North Indian Mound 17872
 
1.1%
Swope Parkway-Elmwood 17792
 
1.1%
Other values (240) 1271475
81.3%
(Missing) 46106
 
2.9%

Length

2023-02-25T10:12:15.661137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
park 147748
 
4.3%
hills 128098
 
3.7%
east 108867
 
3.2%
creek 104581
 
3.0%
blue 98087
 
2.8%
south 98018
 
2.8%
north 94066
 
2.7%
and 77209
 
2.2%
shoal 59166
 
1.7%
oak 59067
 
1.7%
Other values (269) 2476354
71.8%

Most occurring characters

ValueCountFrequency (%)
e 2024521
 
8.9%
1934152
 
8.5%
a 1649498
 
7.3%
o 1561057
 
6.9%
r 1370100
 
6.0%
t 1291903
 
5.7%
l 1174709
 
5.2%
n 1168235
 
5.1%
s 1134269
 
5.0%
i 1065864
 
4.7%
Other values (50) 8340450
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17008571
74.9%
Uppercase Letter 3515573
 
15.5%
Space Separator 1934152
 
8.5%
Decimal Number 140924
 
0.6%
Dash Punctuation 82454
 
0.4%
Other Punctuation 33084
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2024521
11.9%
a 1649498
9.7%
o 1561057
9.2%
r 1370100
 
8.1%
t 1291903
 
7.6%
l 1174709
 
6.9%
n 1168235
 
6.9%
s 1134269
 
6.7%
i 1065864
 
6.3%
h 746484
 
4.4%
Other values (15) 3821931
22.5%
Uppercase Letter
ValueCountFrequency (%)
S 367459
 
10.5%
C 360417
 
10.3%
H 349438
 
9.9%
P 322701
 
9.2%
W 224225
 
6.4%
M 205260
 
5.8%
E 203178
 
5.8%
B 195938
 
5.6%
N 186385
 
5.3%
R 155777
 
4.4%
Other values (13) 944795
26.9%
Decimal Number
ValueCountFrequency (%)
6 37402
26.5%
9 25165
17.9%
4 25165
17.9%
3 25165
17.9%
2 13161
 
9.3%
7 10056
 
7.1%
1 2405
 
1.7%
8 2405
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 19923
60.2%
& 13161
39.8%
Space Separator
ValueCountFrequency (%)
1934152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82454
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20524144
90.4%
Common 2190614
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2024521
 
9.9%
a 1649498
 
8.0%
o 1561057
 
7.6%
r 1370100
 
6.7%
t 1291903
 
6.3%
l 1174709
 
5.7%
n 1168235
 
5.7%
s 1134269
 
5.5%
i 1065864
 
5.2%
h 746484
 
3.6%
Other values (38) 7337504
35.8%
Common
ValueCountFrequency (%)
1934152
88.3%
- 82454
 
3.8%
6 37402
 
1.7%
9 25165
 
1.1%
4 25165
 
1.1%
3 25165
 
1.1%
/ 19923
 
0.9%
2 13161
 
0.6%
& 13161
 
0.6%
7 10056
 
0.5%
Other values (2) 4810
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22714758
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2024521
 
8.9%
1934152
 
8.5%
a 1649498
 
7.3%
o 1561057
 
6.9%
r 1370100
 
6.0%
t 1291903
 
5.7%
l 1174709
 
5.2%
n 1168235
 
5.1%
s 1134269
 
5.0%
i 1065864
 
4.7%
Other values (50) 8340450
36.7%

COUNTY
Categorical

IMBALANCE  MISSING 

Distinct13
Distinct (%)< 0.1%
Missing66959
Missing (%)4.3%
Memory size11.9 MiB
Jackson
1165976 
Clay
248388 
Platte
 
80799
CLAY
 
573
Cass
 
228
Other values (8)
 
292

Length

Max length13
Median length7
Mean length6.4463307
Min length4

Characters and Unicode

Total characters9645361
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowJackson
2nd rowClay
3rd rowJackson
4th rowJackson
5th rowJackson

Common Values

ValueCountFrequency (%)
Jackson 1165976
74.6%
Clay 248388
 
15.9%
Platte 80799
 
5.2%
CLAY 573
 
< 0.1%
Cass 228
 
< 0.1%
JACKSON 219
 
< 0.1%
jackson 41
 
< 0.1%
clay 23
 
< 0.1%
platte 4
 
< 0.1%
Platte County 2
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 66959
 
4.3%

Length

2023-02-25T10:12:15.727724image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
jackson 1166236
77.9%
clay 248984
 
16.6%
platte 80806
 
5.4%
cass 228
 
< 0.1%
county 2
 
< 0.1%
clayl 1
 
< 0.1%
ackson 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
a 1495463
15.5%
s 1166474
12.1%
J 1166195
12.1%
c 1166041
12.1%
o 1166020
12.1%
n 1166020
12.1%
k 1166018
12.1%
l 329218
 
3.4%
C 249411
 
2.6%
y 248414
 
2.6%
Other values (16) 326087
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8146132
84.5%
Uppercase Letter 1499227
 
15.5%
Space Separator 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1495463
18.4%
s 1166474
14.3%
c 1166041
14.3%
o 1166020
14.3%
n 1166020
14.3%
k 1166018
14.3%
l 329218
 
4.0%
y 248414
 
3.0%
t 161612
 
2.0%
e 80805
 
1.0%
Other values (3) 47
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
J 1166195
77.8%
C 249411
 
16.6%
P 80802
 
5.4%
A 793
 
0.1%
L 574
 
< 0.1%
Y 573
 
< 0.1%
K 219
 
< 0.1%
S 219
 
< 0.1%
O 219
 
< 0.1%
N 219
 
< 0.1%
Other values (2) 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9645359
> 99.9%
Common 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1495463
15.5%
s 1166474
12.1%
J 1166195
12.1%
c 1166041
12.1%
o 1166020
12.1%
n 1166020
12.1%
k 1166018
12.1%
l 329218
 
3.4%
C 249411
 
2.6%
y 248414
 
2.6%
Other values (15) 326085
 
3.4%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9645361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1495463
15.5%
s 1166474
12.1%
J 1166195
12.1%
c 1166041
12.1%
o 1166020
12.1%
n 1166020
12.1%
k 1166018
12.1%
l 329218
 
3.4%
C 249411
 
2.6%
y 248414
 
2.6%
Other values (16) 326087
 
3.4%

COUNCIL DISTRICT
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing35242
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean3.7171017
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:15.775862image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5887064
Coefficient of variation (CV)0.42740462
Kurtosis-0.99747228
Mean3.7171017
Median Absolute Deviation (MAD)1
Skewness-0.19876216
Sum5679631
Variance2.5239881
MonotonicityNot monotonic
2023-02-25T10:12:15.827814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 365648
23.4%
5 313864
20.1%
4 269603
17.2%
6 243506
15.6%
1 196785
12.6%
2 138567
 
8.9%
(Missing) 35242
 
2.3%
ValueCountFrequency (%)
1 196785
12.6%
2 138567
 
8.9%
3 365648
23.4%
4 269603
17.2%
5 313864
20.1%
6 243506
15.6%
ValueCountFrequency (%)
6 243506
15.6%
5 313864
20.1%
4 269603
17.2%
3 365648
23.4%
2 138567
 
8.9%
1 196785
12.6%

POLICE DISTRICT
Categorical

Distinct6
Distinct (%)< 0.1%
Missing35265
Missing (%)2.3%
Memory size11.9 MiB
Metro
383130 
East
374326 
Central
234327 
Shoal Creek
209760 
South
201792 

Length

Max length11
Median length7
Mean length5.8854269
Min length4

Characters and Unicode

Total characters8992638
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMetro
2nd rowShoal Creek
3rd rowEast
4th rowEast
5th rowCentral

Common Values

ValueCountFrequency (%)
Metro 383130
24.5%
East 374326
23.9%
Central 234327
15.0%
Shoal Creek 209760
13.4%
South 201792
12.9%
North 124615
 
8.0%
(Missing) 35265
 
2.3%

Length

2023-02-25T10:12:16.084512image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-25T10:12:16.152873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
metro 383130
22.0%
east 374326
21.5%
central 234327
13.5%
shoal 209760
12.1%
creek 209760
12.1%
south 201792
11.6%
north 124615
 
7.2%

Most occurring characters

ValueCountFrequency (%)
t 1318190
14.7%
e 1036977
11.5%
r 951832
10.6%
o 919297
10.2%
a 818413
9.1%
h 536167
 
6.0%
C 444087
 
4.9%
l 444087
 
4.9%
S 411552
 
4.6%
M 383130
 
4.3%
Other values (7) 1728906
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7045168
78.3%
Uppercase Letter 1737710
 
19.3%
Space Separator 209760
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1318190
18.7%
e 1036977
14.7%
r 951832
13.5%
o 919297
13.0%
a 818413
11.6%
h 536167
7.6%
l 444087
 
6.3%
s 374326
 
5.3%
n 234327
 
3.3%
k 209760
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
C 444087
25.6%
S 411552
23.7%
M 383130
22.0%
E 374326
21.5%
N 124615
 
7.2%
Space Separator
ValueCountFrequency (%)
209760
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8782878
97.7%
Common 209760
 
2.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1318190
15.0%
e 1036977
11.8%
r 951832
10.8%
o 919297
10.5%
a 818413
9.3%
h 536167
 
6.1%
C 444087
 
5.1%
l 444087
 
5.1%
S 411552
 
4.7%
M 383130
 
4.4%
Other values (6) 1519146
17.3%
Common
ValueCountFrequency (%)
209760
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8992638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1318190
14.7%
e 1036977
11.5%
r 951832
10.6%
o 919297
10.2%
a 818413
9.1%
h 536167
 
6.0%
C 444087
 
4.9%
l 444087
 
4.9%
S 411552
 
4.6%
M 383130
 
4.3%
Other values (7) 1728906
19.2%

PARCEL ID NO
Real number (ℝ)

SKEWED  ZEROS 

Distinct175953
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106754.49
Minimum0
Maximum9.9589235 × 108
Zeros35266
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:16.230286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3898
Q138358
median85391
Q3136854
95-th percentile228308
Maximum9.9589235 × 108
Range9.9589235 × 108
Interquartile range (IQR)98496

Descriptive statistics

Standard deviation2353178.5
Coefficient of variation (CV)22.042899
Kurtosis76590.509
Mean106754.49
Median Absolute Deviation (MAD)49221
Skewness250.90887
Sum1.6688022 × 1011
Variance5.5374489 × 1012
MonotonicityNot monotonic
2023-02-25T10:12:16.306638image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35266
 
2.3%
12614 4942
 
0.3%
492 2754
 
0.2%
12926 1265
 
0.1%
128568 542
 
< 0.1%
99048 520
 
< 0.1%
98624 450
 
< 0.1%
142693 433
 
< 0.1%
12635 414
 
< 0.1%
127254 360
 
< 0.1%
Other values (175943) 1516269
97.0%
ValueCountFrequency (%)
0 35266
2.3%
1 28
 
< 0.1%
5 13
 
< 0.1%
6 1
 
< 0.1%
7 142
 
< 0.1%
10 30
 
< 0.1%
12 23
 
< 0.1%
14 3
 
< 0.1%
17 72
 
< 0.1%
18 42
 
< 0.1%
ValueCountFrequency (%)
995892354 1
 
< 0.1%
935159351 1
 
< 0.1%
675192432 4
< 0.1%
673306734 1
 
< 0.1%
672126721 1
 
< 0.1%
647706478 1
 
< 0.1%
647476476 1
 
< 0.1%
620486201 1
 
< 0.1%
485674857 1
 
< 0.1%
250613250 3
< 0.1%

LATITUDE
Real number (ℝ)

Distinct157747
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.985272
Minimum35.797519
Maximum39.35464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 MiB
2023-02-25T10:12:16.382212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35.797519
5-th percentile38.915251
Q138.997002
median39.054552
Q339.109302
95-th percentile39.257015
Maximum39.35464
Range3.557121
Interquartile range (IQR)0.1123

Descriptive statistics

Standard deviation0.52951741
Coefficient of variation (CV)0.013582499
Kurtosis31.132856
Mean38.985272
Median Absolute Deviation (MAD)0.056051
Skewness-5.6446435
Sum60942361
Variance0.28038868
MonotonicityNot monotonic
2023-02-25T10:12:16.454736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.797519 40610
 
2.6%
39.100387 4940
 
0.3%
39.014493 2469
 
0.2%
39.099123 1246
 
0.1%
39.074934 476
 
< 0.1%
39.285963 380
 
< 0.1%
39.031378 374
 
< 0.1%
39.100349 371
 
< 0.1%
39.307933 360
 
< 0.1%
39.074825 312
 
< 0.1%
Other values (157737) 1511677
96.7%
ValueCountFrequency (%)
35.797519 40610
2.6%
38.827084 1
 
< 0.1%
38.83482 5
 
< 0.1%
38.835025 6
 
< 0.1%
38.838219 29
 
< 0.1%
38.838324 5
 
< 0.1%
38.838331 34
 
< 0.1%
38.838343 3
 
< 0.1%
38.838587 8
 
< 0.1%
38.838841 4
 
< 0.1%
ValueCountFrequency (%)
39.35464 5
 
< 0.1%
39.354635 2
 
< 0.1%
39.354631 1
 
< 0.1%
39.354629 6
 
< 0.1%
39.354601 3
 
< 0.1%
39.354591 5
 
< 0.1%
39.354575 16
< 0.1%
39.353859 1
 
< 0.1%
39.353853 3
 
< 0.1%
39.353638 1
 
< 0.1%

LONGITUDE
Real number (ℝ)

Distinct126281
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-94.792875
Minimum-103.89058
Maximum-94.386375
Zeros0
Zeros (%)0.0%
Negative1563215
Negative (%)100.0%
Memory size11.9 MiB
2023-02-25T10:12:16.531581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-103.89058
5-th percentile-94.645131
Q1-94.583575
median-94.55375
Q3-94.523262
95-th percentile-94.474424
Maximum-94.386375
Range9.504204
Interquartile range (IQR)0.060313

Descriptive statistics

Standard deviation1.4864643
Coefficient of variation (CV)-0.015681181
Kurtosis33.45319
Mean-94.792875
Median Absolute Deviation (MAD)0.030071
Skewness-5.9512036
Sum-1.4818164 × 108
Variance2.209576
MonotonicityNot monotonic
2023-02-25T10:12:16.607168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-103.890579 40610
 
2.6%
-94.577919 4958
 
0.3%
-94.529933 2472
 
0.2%
-94.577983 1246
 
0.1%
-94.591904 481
 
< 0.1%
-94.576776 414
 
< 0.1%
-94.472954 378
 
< 0.1%
-94.540878 372
 
< 0.1%
-94.59448 370
 
< 0.1%
-94.588552 320
 
< 0.1%
Other values (126271) 1511594
96.7%
ValueCountFrequency (%)
-103.890579 40610
2.6%
-94.756681 1
 
< 0.1%
-94.756298 1
 
< 0.1%
-94.754146 1
 
< 0.1%
-94.752204 1
 
< 0.1%
-94.752202 1
 
< 0.1%
-94.752171 12
 
< 0.1%
-94.75217 2
 
< 0.1%
-94.752163 8
 
< 0.1%
-94.752122 2
 
< 0.1%
ValueCountFrequency (%)
-94.386375 26
< 0.1%
-94.386377 2
 
< 0.1%
-94.386465 1
 
< 0.1%
-94.386516 13
< 0.1%
-94.386648 12
< 0.1%
-94.386673 1
 
< 0.1%
-94.386677 8
 
< 0.1%
-94.386711 3
 
< 0.1%
-94.386814 2
 
< 0.1%
-94.386906 2
 
< 0.1%

CASE URL
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct1563215
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.9 MiB
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019119972
 
1
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015045877
 
1
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015040302
 
1
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015041682
 
1
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015049038
 
1
Other values (1563210)
1563210 

Length

Max length91
Median length75
Mean length75.007103
Min length75

Characters and Unicode

Total characters117252229
Distinct characters43
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1563215 ?
Unique (%)100.0%

Sample

1st rowhttp://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019119972
2nd rowhttp://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019207923
3rd rowhttp://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2021005976
4th rowhttp://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2020149407
5th rowhttp://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2020054721

Common Values

ValueCountFrequency (%)
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019119972 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015045877 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015040302 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015041682 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015049038 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015034811 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015041579 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015042453 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015052481 1
 
< 0.1%
http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015043953 1
 
< 0.1%
Other values (1563205) 1563205
> 99.9%

Length

2023-02-25T10:12:16.743896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2019119972 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2019208975 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2020054721 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2019182182 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2019184705 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2019184590 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2020095175 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2015094486 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2020021142 1
 
< 0.1%
http://city.kcmo.org/kc/actioncenterrequest/caseinfo.aspx?caseid=2020086645 1
 
< 0.1%
Other values (1563205) 1563205
> 99.9%

Most occurring characters

ValueCountFrequency (%)
e 9379984
 
8.0%
t 9378596
 
8.0%
/ 7816075
 
6.7%
o 6254942
 
5.3%
s 6254248
 
5.3%
c 6252860
 
5.3%
n 4691033
 
4.0%
a 4689645
 
4.0%
. 4689645
 
4.0%
C 4689645
 
4.0%
Other values (33) 53155556
45.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 71918994
61.3%
Other Punctuation 15632150
 
13.3%
Decimal Number 15632150
 
13.3%
Uppercase Letter 12505720
 
10.7%
Math Symbol 1563215
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 9379984
13.0%
t 9378596
13.0%
o 6254942
8.7%
s 6254248
 
8.7%
c 6252860
 
8.7%
n 4691033
 
6.5%
a 4689645
 
6.5%
p 3127124
 
4.3%
i 3127124
 
4.3%
r 3126430
 
4.3%
Other values (13) 15637008
21.7%
Decimal Number
ValueCountFrequency (%)
0 3757171
24.0%
2 2729759
17.5%
1 2605774
16.7%
9 1022088
 
6.5%
8 999282
 
6.4%
3 946917
 
6.1%
7 941128
 
6.0%
5 883944
 
5.7%
4 881469
 
5.6%
6 864618
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
C 4689645
37.5%
I 3126430
25.0%
D 1563215
 
12.5%
R 1563215
 
12.5%
A 1563215
 
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 7816075
50.0%
. 4689645
30.0%
? 1563215
 
10.0%
: 1563215
 
10.0%
Math Symbol
ValueCountFrequency (%)
= 1563215
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 84424714
72.0%
Common 32827515
 
28.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 9379984
 
11.1%
t 9378596
 
11.1%
o 6254942
 
7.4%
s 6254248
 
7.4%
c 6252860
 
7.4%
n 4691033
 
5.6%
a 4689645
 
5.6%
C 4689645
 
5.6%
p 3127124
 
3.7%
i 3127124
 
3.7%
Other values (18) 26579513
31.5%
Common
ValueCountFrequency (%)
/ 7816075
23.8%
. 4689645
14.3%
0 3757171
11.4%
2 2729759
 
8.3%
1 2605774
 
7.9%
= 1563215
 
4.8%
? 1563215
 
4.8%
: 1563215
 
4.8%
9 1022088
 
3.1%
8 999282
 
3.0%
Other values (5) 4518076
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117252229
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 9379984
 
8.0%
t 9378596
 
8.0%
/ 7816075
 
6.7%
o 6254942
 
5.3%
s 6254248
 
5.3%
c 6252860
 
5.3%
n 4691033
 
4.0%
a 4689645
 
4.0%
. 4689645
 
4.0%
C 4689645
 
4.0%
Other values (33) 53155556
45.3%
Distinct4
Distinct (%)< 0.1%
Missing1550513
Missing (%)99.2%
Memory size11.9 MiB
0.0
7388 
90.0
4597 
30.0
 
415
60.0
 
302

Length

Max length4
Median length3
Mean length3.4183593
Min length3

Characters and Unicode

Total characters43420
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 7388
 
0.5%
90.0 4597
 
0.3%
30.0 415
 
< 0.1%
60.0 302
 
< 0.1%
(Missing) 1550513
99.2%

Length

2023-02-25T10:12:16.812937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-25T10:12:16.872969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.0 7388
58.2%
90.0 4597
36.2%
30.0 415
 
3.3%
60.0 302
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25404
58.5%
. 12702
29.3%
9 4597
 
10.6%
3 415
 
1.0%
6 302
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30718
70.7%
Other Punctuation 12702
29.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25404
82.7%
9 4597
 
15.0%
3 415
 
1.4%
6 302
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 12702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25404
58.5%
. 12702
29.3%
9 4597
 
10.6%
3 415
 
1.0%
6 302
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25404
58.5%
. 12702
29.3%
9 4597
 
10.6%
3 415
 
1.0%
6 302
 
0.7%

Interactions

2023-02-25T10:11:56.310958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:20.755529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:24.319613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:27.959061image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:31.463332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:35.087661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:38.546210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:42.025220image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:45.624653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:49.197010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:52.644905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:56.632431image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:21.091518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:24.738820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:28.271562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:31.797621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:35.414533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:38.872888image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:42.366897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:45.956682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:49.508402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:52.993100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:56.948273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:21.401534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:25.056997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:28.576905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:32.119332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:35.732883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:39.188904image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:42.681097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:46.280449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:49.804428image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:53.329011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:57.255959image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:21.736635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:25.387106image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:28.901440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:32.439680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:36.052548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:39.514495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:43.020826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:46.605602image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:50.121789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:53.666133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:57.556625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:22.055873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:25.707850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:29.215515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:32.760330image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:36.361253image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:39.825747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:43.319237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:46.918477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:50.430303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:53.988675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:57.862396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:22.376014image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:26.029963image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:29.532792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:33.081411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:36.672375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:40.137036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:43.637722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:47.240424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:50.743447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:54.316782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:58.187364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:22.697595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:26.361928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:29.851179image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:33.391133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:36.974958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:40.448998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:43.939011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:47.557653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:51.058612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:54.640260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:58.489531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:23.011637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:26.681527image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:30.164313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:33.706187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:37.277147image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:40.749577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:44.237325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:47.877282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:51.366669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:54.967174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:58.802212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:23.326344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:27.000816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:30.476365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:34.109884image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:37.600476image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:41.063597image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:44.549679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:48.206249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:51.673373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:55.304718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:59.117168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:23.670678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:27.329246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:30.805990image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:34.443931image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:37.915940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:41.375686image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:44.880045image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:48.532891image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:51.988816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:55.644893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:59.430435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:23.999183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:27.658055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:31.131135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:34.768907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:38.228798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:41.686365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:45.206883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:48.856577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:52.306634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2023-02-25T10:11:55.989829image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Missing values

2023-02-25T10:12:00.671311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-02-25T10:12:03.832044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-02-25T10:12:10.318492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

CASE IDSOURCEDEPARTMENTWORK GROUPREQUEST TYPECATEGORYTYPEDETAILCREATION DATECREATION TIMECREATION MONTHCREATION YEARSTATUSEXCEEDED EST TIMEFRAMECLOSED DATECLOSED MONTHCLOSED YEARDAYS TO CLOSESTREET ADDRESSADDRESS WITH GEOCODEZIP CODENEIGHBORHOODCOUNTYCOUNCIL DISTRICTPOLICE DISTRICTPARCEL ID NOLATITUDELONGITUDECASE URL30-60-90 Days Open Window
02019119972PHONENHSNHS-Dangerous Buildings-Prop/Build/Construct-Dangerous Building-On listProperty / Buildings / ConstructionDangerous BuildingStandard06/24/201907:40 AM62019RESOLY11/19/202111.02021.0879.02317 E 50th St2317 E 50th St64130\n(39.035489, -94.557309)64130.0Blue HillsJackson3.0Metro13886339.035489-94.557309http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019119972NaN
12019207923WEBPublic WorksPublic Works-Street and Traffic-District 1Streets / Roadways / Alleys-Crack-District 1Streets / Roadways / AlleysCrackDistrict 112/22/201907:56 PM122019RESOLY06/26/20206.02020.0187.010329 N Forest Ave10329 N Forest Ave64155\n(39.28196, -94.564453)64155.0New MarkClay2.0Shoal Creek10370339.281960-94.564453http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019207923NaN
22021005976PHONENHSNHS-Dangerous Buildings-Prop/Build/Construct-Dangerous Building-On listProperty / Buildings / ConstructionDangerous BuildingStandard01/19/202102:43 PM12021RESOLY11/15/202111.02021.0300.02623 E 10th St2623 E 10th St64127\n(39.101272, -94.549951)64127.0Independence PlazaJackson3.0East1070339.101272-94.549951http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2021005976NaN
32020149407PHONENHSNHS-Neighborhood Preservation-Property ViolationsProperty / Buildings / ConstructionProperty MaintenanceOther Property Issue11/25/202009:19 AM112020RESOLY04/26/20214.02021.0152.02474 Chelsea Ave2474 Chelsea Ave64127\n(39.079895, -94.526959)64127.0East Community Team SouthJackson3.0East1917839.079895-94.526959http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2020149407NaN
42020054721WEBParks and RecParks and Rec-Central Region-Parks & Recreation-Park Maintenance-CentralParks & RecreationPark MaintenanceCentral04/18/202005:10 PM42020RESOLN04/30/20204.02020.012.0400 W 31st St400 W 31st St64108\n(39.074934, -94.591904)64108.0Westside SouthJackson4.0Central12856839.074934-94.591904http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2020054721NaN
52019182182PHONENHSNHS-Dangerous Buildings-Prop/Build/Construct-Dangerous Building-On listProperty / Buildings / ConstructionDangerous BuildingStandard10/21/201910:29 AM102019RESOLY08/03/20208.02020.0287.04043 Kenwood Ave4043 Kenwood Ave64110\n(39.052983, -94.577808)64110.0South Hyde ParkJackson4.0Central13329139.052983-94.577808http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019182182NaN
62019184705WEBNHSNHS-Solid Waste-Trash / Recycling-Recycling-Missed by CityTrash / RecyclingRecyclingMissed by City10/25/201910:02 AM102019RESOLN10/28/201910.02019.03.0637 E 62nd St637 E 62nd St64110\n(39.01416, -94.579673)64110.0Western 49-63Jackson6.0Metro10610639.014160-94.579673http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019184705NaN
72019184590WEBParks and RecParks and Rec-Landscape Services-ForestryTrees-Trimming-Tree LimbsTreesTrimmingTree Limbs10/25/201904:44 AM102019RESOLY12/04/201912.02019.040.010901 Blue Ridge Blvd10901 Blue Ridge Blvd64134\n(38.924085, -94.507192)64134.0Ruskin HeightsJackson6.0South5954638.924085-94.507192http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019184590NaN
82020095175PHONENHSNHS-Dangerous Buildings-Prop/Build/Construct-Dangerous Building-On listProperty / Buildings / ConstructionDangerous BuildingStandard07/13/202008:00 AM72020RESOLY11/29/202111.02021.0504.04215 E 60th St4215 E 60th St64130\n(39.016565, -94.536611)64130.0Swope Parkway-ElmwoodJackson5.0Metro32639.016565-94.536611http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2020095175NaN
92015094486PHONENHSNHS-Solid Waste-AdministrationTrash / Recycling-Services-Service Issue / ProblemTrash / RecyclingServicesService Issue / Problem08/07/201501:45 PM82015RESOLY05/27/20165.02016.0294.04518 N Askew Ave4518 N Askew Ave64117\n(39.176846, -94.537416)64117.0Antioch AcresClay1.0Shoal Creek7694639.176846-94.537416http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2015094486NaN
CASE IDSOURCEDEPARTMENTWORK GROUPREQUEST TYPECATEGORYTYPEDETAILCREATION DATECREATION TIMECREATION MONTHCREATION YEARSTATUSEXCEEDED EST TIMEFRAMECLOSED DATECLOSED MONTHCLOSED YEARDAYS TO CLOSESTREET ADDRESSADDRESS WITH GEOCODEZIP CODENEIGHBORHOODCOUNTYCOUNCIL DISTRICTPOLICE DISTRICTPARCEL ID NOLATITUDELONGITUDECASE URL30-60-90 Days Open Window
15632052019175846PHONEParks and RecParks and Rec-Landscape Services-ForestryTrees-Removal-DecliningTreesRemovalDeclining10/04/201911:35 AM102019RESOLY12/04/201912.02019.061.03942 Wyandotte St3942 Wyandotte St64111\n(39.055001, -94.588843)64111.0Old WestportJackson4.0Central13264439.055001-94.588843http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019175846NaN
15632062019175727PHONEParks and RecParks and Rec-Landscape Services-ForestryTrees-Removal-Tree LimbsTreesRemovalTree Limbs10/04/201909:32 AM102019RESOLY11/05/201911.02019.032.09014 E 88th Ter9014 E 88th Ter64138\n(38.962712, -94.478245)64138.0White OakJackson5.0South6640838.962712-94.478245http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019175727NaN
15632072019176019PHONEParks and RecParks and Rec-Landscape Services-ForestryTrees-Trimming-Block PruningTreesTrimmingBlock Pruning10/04/201903:51 PM102019RESOLN10/11/201910.02019.07.09208 NE 109th Ct9208 NE 109th Ct64157\n(39.289643, -94.46439)64157.0Shoal CreekClay1.0Shoal Creek20967839.289643-94.464390http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019176019NaN
15632082019175967PHONEParks and RecParks and Rec-Landscape Services-ForestryTrees-Trimming-Tree LimbsTreesTrimmingTree Limbs10/04/201902:46 PM102019RESOLY10/30/201910.02019.026.03106 Peery Ave3106 Peery Ave64127\n(39.099803, -94.545545)64127.0Independence PlazaJackson3.0East1087639.099803-94.545545http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019175967NaN
15632092019175920PHONEParks and RecParks and Rec-Landscape Services-ForestryTrees-Trimming-Tree LimbsTreesTrimmingTree Limbs10/04/201901:04 PM102019RESOLY10/19/201910.02019.015.05048 NE 56th Pl5048 NE 56th Pl64119\n(39.195871, -94.518434)64119.0Ravenwood-SomersetClay1.0Shoal Creek9040839.195871-94.518434http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019175920NaN
15632102019175624PHONENHSNHS-Solid Waste-Trash / Recycling-Trash Collection-Missed by Contractor NorthTrash / RecyclingTrash CollectionMissed by Contractor North10/03/201906:18 PM102019RESOLN10/05/201910.02019.02.010415 NW 87th St10415 NW 87th St64153\n(39.251356, -94.702155)64153.0KCI & 2nd CreekPlatte2.0North21172439.251356-94.702155http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019175624NaN
15632112019176099PHONEParks and RecParks and Rec-Central Region-Parks & Recreation-Park Maintenance-CentralParks & RecreationPark MaintenanceCentral10/05/201908:13 AM102019RESOLN10/10/201910.02019.05.02308 Topping Ave2308 Topping Ave64127\n(39.082634, -94.515668)64127.0South Blue ValleyJackson3.0East2011839.082634-94.515668http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019176099NaN
15632122019176030PHONENHSNHS-Solid Waste-Animals / Pets-Dead Animal -CurbAnimals / PetsDead AnimalCurb10/04/201904:07 PM102019RESOLN10/05/201910.02019.01.05437 South Benton Ave5437 South Benton Ave64130\n(39.026897, -94.551349)64130.0North Town Fork CreekJackson5.0Metro3626539.026897-94.551349http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019176030NaN
15632132019176115PHONEPublic WorksPublic Works-Capital Projects-Traffic PermitsStreets / Roadways / Alleys-Plate-Missing / DisplacedStreets / Roadways / AlleysPlateMissing / Displaced10/05/201904:50 PM102019RESOLY12/04/201912.02019.060.01201 W 75th St1201 W 75th St64114\n(38.992568, -94.604029)64114.0Ward ParkwayJackson6.0Metro12044438.992568-94.604029http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019176115NaN
15632142019172858WEBCity Planning and DevelopmentCity Planning and Development-Permit Compliance-Prop/Build/Construct-Construction Issue/Concern-Work without permitProperty / Buildings / ConstructionConstruction Issue/ConcernWork Without Permit09/27/201908:01 PM92019RESOLY10/06/201910.02019.09.010799 NW Skyview Ave10799 NW Skyview Ave64154\n(39.288525, -94.651254)64154.0KCI & 2nd CreekPlatte2.0North20775639.288525-94.651254http://city.kcmo.org/kc/ActionCenterRequest/CaseInfo.aspx?CaseID=2019172858NaN